Within-field Management Zoning Baltics

Spending on fertilisers and agrochemicals represents a considerable part of farmers’ overall expenditure. By using hyperspectral imaging to detect what nutrients and how much of them a crop needs in the different growth stages, such costs can be reduced. Hyperspectral imaging is the process of creating an image through electromagnetic radiation, carried out by an automated drone system. The use case demonstrates both in potato as well as wheat farms how data from different types of sensors - measuring parameters such as soil moisture and organic matter or climate conditions – combined with spectral data analysis can be used for precise decision-making and optimised crop management. The data gathered enables farmers to predict yields, define specific management zones, and accurately calculate the required fertilisers, herbicides and other agrochemical products. This use case thus delivers an innovative solution to pressing issues in arable farming.

-20%

soil fertility loss

+5%

crop yield

-70%

field analysis time and cost

Specific goals

  • Fast and cost-efficient way to detect the amounts of micro and macro nutritional elements needed in plants;
  • Automatic recommendations for agrochemical application;
  • Early detection of plant stress and its causes;
  • Non-invasive, remote sensing technology;
  • Analysis of large amounts of data for precise decision-making;
  • Add new technology to the related Within-field Management Zoning use case, through hyperspectral sensor data for fertiliser management.

Expected results

  • Field analysis time and cost -70%
  • Fertiliser cost reduction 40€ / ha
  • Soil fertility loss -20%
  • Crop yields gains +5%
  • Classified data increase x8

Additional material

  • Use case poster

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